TY - JOUR
T1 - The generalized birnbaum-saunders distribution and its theory, methodology, and application
AU - Sanhueza, Antonio
AU - Leiva, Víctor
AU - Balakrishnan, N.
N1 - Funding Information:
The authors thank the editor and referees for their helpful comments that allow to improve this article. This study was partially supported by Grants FONDECYT 1050862 and DIUFRO 120621, Chile.
PY - 2008/3
Y1 - 2008/3
N2 - In this paper, we discuss the class of generalized Birnbaum-Saunders distributions, which is a very flexible family suitable for modeling lifetime data as it allows for different degrees of kurtosis and asymmetry and unimodality as well as bimodality. We describe the theoretical developments on this model including properties, transformations and related distributions, lifetime analysis, and shape analysis. We also discuss methods of inference based on uncensored and censored data, diagnostics methods, goodness-of-fit tests, and random number generation algorithms for the generalized Birnbaum-Saunders model. Finally, we present some illustrative examples and show that this distribution fits the data better than the classical Birnbaum-Saunders model.
AB - In this paper, we discuss the class of generalized Birnbaum-Saunders distributions, which is a very flexible family suitable for modeling lifetime data as it allows for different degrees of kurtosis and asymmetry and unimodality as well as bimodality. We describe the theoretical developments on this model including properties, transformations and related distributions, lifetime analysis, and shape analysis. We also discuss methods of inference based on uncensored and censored data, diagnostics methods, goodness-of-fit tests, and random number generation algorithms for the generalized Birnbaum-Saunders model. Finally, we present some illustrative examples and show that this distribution fits the data better than the classical Birnbaum-Saunders model.
KW - Censored data
KW - Goodness-of-fit
KW - Inference and diagnostics
KW - Lifetime analysis
KW - Robustness
KW - Simulation algorithm
UR - http://www.scopus.com/inward/record.url?scp=35748945633&partnerID=8YFLogxK
U2 - 10.1080/03610920701541174
DO - 10.1080/03610920701541174
M3 - Article
AN - SCOPUS:35748945633
SN - 0361-0926
VL - 37
SP - 645
EP - 670
JO - Communications in Statistics - Theory and Methods
JF - Communications in Statistics - Theory and Methods
IS - 5
ER -